R Notebook
About this file Data Fields:
Battery: The capacity of the vehicle’s battery in kilowatt-hours (kWh).
Car_name: The model name of the electric vehicle.
Car_name_link: A direct link to the corresponding page on EV Database for more in-depth information.
Efficiency: The energy efficiency rating of the vehicle in watt-hours per kilometer (Wh/km).
Fast_charge: The fast-charging capability of the vehicle in minutes for a certain charging percentage.
Price.DE.:The price of the electric vehicle in Germany.
Range: The driving range of the vehicle on a single charge in kilometers.
Top_speed:The maximum speed the vehicle can achieve in kilometers per hour.
Acceleration..0.100.: The acceleration time from 0 to 100 kilometers per hour.
library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, unionlibrary(ggplot2)Warning: package ‘ggplot2’ was built under R version 4.3.2library(tidyr)
Attaching package: ‘tidyr’
The following object is masked _by_ ‘.GlobalEnv’:
billboardlibrary(car)Warning: package ‘car’ was built under R version 4.3.2Loading required package: carData
Warning: package ‘carData’ was built under R version 4.3.2
Attaching package: ‘car’
The following object is masked from ‘package:dplyr’:
recodelibrary(MASS)
Attaching package: ‘MASS’
The following object is masked from ‘package:dplyr’:
selectlibrary(repr)Warning: package ‘repr’ was built under R version 4.3.2install.packages('pals')WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:
https://cran.rstudio.com/bin/windows/Rtools/
Installing package into ‘C:/Users/Natalie/AppData/Local/R/win-library/4.3’
(as ‘lib’ is unspecified)
trying URL 'https://cran.rstudio.com/bin/windows/contrib/4.3/pals_1.8.zip'
Content type 'application/zip' length 1905378 bytes (1.8 MB)
downloaded 1.8 MBpackage ‘pals’ successfully unpacked and MD5 sums checked
The downloaded binary packages are in
C:\Users\Natalie\AppData\Local\Temp\RtmpeUeyj3\downloaded_packageslibrary(pals)Warning: package ‘pals’ was built under R version 4.3.2install.packages('broom')Error in install.packages : Updating loaded packagesecars_raw = read.csv('EV_cars.csv')
ecars_rawNA#rename some of the columns
ecars_raw = ecars_raw %>% rename(Price = Price.DE., Acceleration = acceleration..0.100.)
# extract the Make of each car into its own column
make = strsplit(ecars_raw$Car_name, split = ' ')
make_ = c()
n = length(make)
for (i in 1:n) {
make_[i] = make[[i]][1]
}
ecars_raw$Make = make_# move columns so continuous variables are together
ecars_raw = ecars_raw %>% relocate(Make, .before = Car_name_link)
ecars_raw = ecars_raw %>% relocate(Battery, .after = Car_name_link)
ecars_rawecars_raw = ecars_raw %>% filter(!is.na(Fast_charge))
ecars = ecars_raw %>% filter(!is.na(Price))
ecars_missing_price = ecars_raw %>% filter(is.na(Price))This data required minimal processing. I created a Make variable by extracting the first word from the Car_name variable. I also renamed several columns to make them more intuitive for example acceleration..0.100. to Acceleration. I removed the two cars that did not have Fast Charge (the Renault Twingo Electric and the e.Go e.wave X) capability because this was an important feature in the linear regression and was impacting their price. Finally I made sure all the continuous variables were next to each other to simplify calling them. I split the dataframe into two. One with prices(307 objects) and one with missing prices (51 objects).
After cleaning the data 45 unique car makes were included in the ecars data used to create the linear model and 22 unique car makes were included in the data with missing prices. Additionally 14 makes that have 10 or more car models are highlighted throughout the project.
length(ecars$Price)
[1] 307ecars$upper.limit
NULL
BatvRange
BatvPrice
AccvPrice
Colinearity with predicting Range based n battery
ecars %>% group_by(Make) %>%
filter(n() >= 10) %>%o
ggplot(., aes(x = Battery, y = Price)) +
RBmodel = lm(Range ~ Battery, data = ecars)
summary(RBmodel)
Call:
lm(formula = Range ~ Battery, data = ecars)
Residuals:
Min 1Q Median 3Q Max
-152.015 -27.740 6.636 34.682 123.700
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 39.1986 10.8427 3.615 0.000351 ***
Battery 4.6424 0.1461 31.780 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 52.04 on 305 degrees of freedom
Multiple R-squared: 0.7681, Adjusted R-squared: 0.7673
F-statistic: 1010 on 1 and 305 DF, p-value: < 2.2e-16plot(RBmodel) 
PBmodel = lm(Price ~ Battery, data = ecars)
summary(PBmodel)
Call:
lm(formula = Price ~ Battery, data = ecars)
Residuals:
Min 1Q Median 3Q Max
-52248 -13991 -4777 7763 117008
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -17283.30 5122.18 -3.374 0.000836 ***
Battery 1188.09 69.01 17.216 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 24580 on 305 degrees of freedom
Multiple R-squared: 0.4929, Adjusted R-squared: 0.4912
F-statistic: 296.4 on 1 and 305 DF, p-value: < 2.2e-16plot(PBmodel) 
ATmodel = lm(Top_speed ~ Acceleration, data = ecars)
summary(ATmodel)
Call:
lm(formula = Top_speed ~ Acceleration, data = ecars)
Residuals:
Min 1Q Median 3Q Max
-38.133 -14.247 -3.351 11.352 61.413
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 253.9440 2.8706 88.46 <2e-16 ***
Acceleration -9.9663 0.3633 -27.43 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 19.62 on 305 degrees of freedom
Multiple R-squared: 0.7116, Adjusted R-squared: 0.7107
F-statistic: 752.6 on 1 and 305 DF, p-value: < 2.2e-16plot(ATmodel)
model = lm(Price_pow ~ Efficiency_pow + Range + Speed_pow + Fast_charge, data = ecars)
summary(model)
Call:
lm(formula = Price_pow ~ Efficiency_pow + Range + Speed_pow +
Fast_charge, data = ecars)
Residuals:
Min 1Q Median 3Q Max
-7.126e-04 -2.348e-04 -3.221e-05 2.337e-04 1.205e-03
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.390e-02 7.794e-04 30.670 < 2e-16 ***
Efficiency_pow -3.138e-03 1.327e-04 -23.654 < 2e-16 ***
Range -2.586e-06 2.931e-07 -8.821 < 2e-16 ***
Speed_pow -1.832e-03 1.984e-04 -9.237 < 2e-16 ***
Fast_charge -7.379e-07 1.340e-07 -5.506 7.87e-08 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.0003282 on 302 degrees of freedom
Multiple R-squared: 0.841, Adjusted R-squared: 0.8389
F-statistic: 399.2 on 4 and 302 DF, p-value: < 2.2e-16plot(model)
#battery speed_pow efficiency and fast charge
With transformation done to price
ecars_missing_price$Speed_pow = (ecars_missing_price$Top_speed ** .25)
ecars_missing_price$Efficiency_pow = (ecars_missing_price$Efficiency ** .25)
test = predict(model, ecars_missing_price, interval = 'prediction')
test_2_dollars = (1/(test))^2
ecars_missing_pricetest_2_dollars fit lwr upr
1 114303.84 188896.41 76531.58
2 89113.37 137384.99 62443.12
3 55619.74 77576.44 41819.01
4 54659.60 75919.87 41223.42
5 47757.60 64889.53 36612.56
6 35948.52 46773.09 28488.93
7 82964.83 125423.41 58914.43
8 72005.39 105794.99 52153.52
9 116264.67 193134.93 77588.69
10 62155.39 88708.61 45958.31
11 51529.20 70813.69 39170.12
12 72409.64 106452.41 52424.37
13 51529.20 70813.69 39170.12
14 75973.53 112737.12 54647.63
15 72695.12 106821.49 52648.56
16 62336.75 88673.56 46202.47
17 80566.83 121343.96 57358.50
18 58613.51 82453.04 43795.56
19 89458.26 138273.53 62575.80
20 66785.24 96353.75 49000.18
21 81626.52 123050.92 58076.92
22 50205.93 68693.77 38288.94
23 57039.24 79877.89 42759.68
24 38018.75 49838.12 29954.77
25 71684.84 105545.90 51844.75
26 91085.12 141305.37 63557.03
27 53897.40 74798.88 40673.54
28 50205.93 68693.77 38288.94
29 86129.38 131353.77 60796.64
30 64293.64 92120.53 47405.71
31 148097.01 268259.59 93731.09
32 47913.40 65059.31 36749.78
33 42545.76 56726.05 33087.13
34 50922.36 69841.50 38765.85
35 98325.01 155665.09 67688.90
36 82807.58 125301.65 58765.47
37 34214.65 44253.67 27241.08
38 56100.49 78282.57 42166.40
39 36394.05 47428.21 28806.23
40 60441.11 85513.51 44973.03
41 44078.10 59166.88 34103.20
42 60763.89 86018.70 45194.71
43 67192.92 97054.78 49258.43
44 41602.07 55261.29 32445.70
45 27648.07 34838.28 22474.16
46 35005.02 45428.65 27796.95
47 33276.68 42906.07 26559.49
48 55272.82 77121.78 41546.62
49 49975.26 68511.06 38057.87
50 56337.02 78895.92 42232.70
51 48372.20 65925.83 36998.79ecars_missing_price$predicted_price = (test_2_dollars[,1])
ecars_missing_pricetest2 = predict(model, ecars, interval = 'prediction')
test3 = predict(model, ecars, interval = 'confidence')
test2_2_dollars = (1/(test2))^2
test3_2_dollars = (1/(test3))^2
test2_2_dollars fit lwr upr
1 66145.66 95294.44 48580.54
2 45919.82 62037.58 35355.21
3 44897.70 60325.70 34711.68
4 46366.59 62669.37 35687.07
5 57783.36 81202.29 43207.43
6 53860.25 74816.12 40617.95
7 63380.73 90573.13 46821.27
8 50511.32 69183.64 38491.92
9 34987.91 45341.08 27814.71
10 56245.60 78643.63 42212.94
11 60322.87 85510.97 44822.36
12 41849.83 55663.04 32606.32
13 49975.06 68330.72 38132.52
14 43291.62 57893.72 33590.32
15 78777.40 118266.99 56209.15
16 44574.90 59862.51 34474.98
17 108138.96 175847.21 73156.59
18 58558.78 82322.78 43775.30
19 33627.90 43372.65 26833.12
20 58391.34 82221.31 43598.31
21 92139.96 143223.47 64208.33
22 43486.93 58155.33 33741.68
23 42132.06 56066.25 32813.74
24 26018.13 32536.69 21278.94
25 63291.41 90383.37 46778.39
26 75083.89 111076.00 54123.24
27 42390.29 56471.40 32987.35
28 51651.83 71029.73 39243.81
29 109166.29 177067.64 73972.74
30 49115.76 66954.13 37561.25
31 44547.48 59853.56 34441.61
32 52372.98 72180.79 39726.46
33 69150.75 101164.83 50237.62
34 55485.91 77381.56 41721.63
35 92450.64 143587.49 64460.56
36 92396.16 143509.17 64420.67
37 39846.85 52587.30 31232.21
38 55435.06 77345.08 41669.78
39 56686.11 79306.56 42525.08
40 45525.12 61343.75 35120.65
41 41877.97 55677.63 32638.48
42 33947.67 43847.49 27057.97
43 97561.04 153511.46 67435.76
44 36698.50 47878.64 29021.83
45 119945.79 200724.10 79673.26
46 51387.12 70753.32 39006.77
47 74363.73 109941.32 53627.71
48 31254.70 39971.72 25106.80
49 50017.16 68448.82 38139.44
50 67020.44 97652.54 48829.17
51 108668.84 177371.31 73338.11
52 64053.49 92989.92 46788.18
53 38574.96 50685.41 30338.11
54 58650.78 82665.66 43761.55
55 32870.15 42263.28 26293.01
56 57421.49 80582.90 42979.95
57 58277.47 81902.79 43574.52
58 77051.01 114638.46 55320.93
59 36394.05 47428.21 28806.23
60 137238.83 239824.73 88749.16
61 52531.85 72507.49 39803.06
62 71684.84 105545.90 51844.75
63 58367.40 82260.56 43552.30
64 44758.82 60135.91 34605.70
65 36829.29 48073.55 29113.82
66 161878.33 298003.91 101484.70
67 64367.45 92204.84 47468.06
68 51621.91 70962.68 39231.73
69 47207.74 63957.33 36269.77
70 47392.47 64459.97 36304.47
71 39251.21 51687.21 30817.67
72 60172.15 85155.95 44764.13
73 55098.13 76633.83 41512.27
74 51537.76 70825.89 39176.45
75 95349.28 150116.22 65882.25
76 90724.23 140365.18 63420.34
77 63246.89 90232.05 46778.20
78 75011.12 111038.51 54046.94
79 54993.54 76600.44 41388.86
80 79847.51 119870.21 56973.78
81 112711.37 185108.32 75765.86
82 70568.44 103630.87 51131.05
83 45478.70 61346.25 35056.70
84 32150.11 41237.00 25766.51
85 69806.96 101792.80 50831.04
86 33179.82 42749.22 26497.76
87 87954.60 135098.37 61785.13
88 35166.68 45627.02 27930.79
89 85531.70 130436.23 60376.65
90 51537.76 70825.89 39176.45
91 103915.93 166712.86 70918.29
92 47878.71 65067.78 36699.60
93 72079.29 106230.58 52094.31
94 42236.80 56237.87 32880.89
95 114174.19 188590.51 76468.42
96 65364.07 93853.42 48121.65
97 53813.43 74655.20 40621.06
98 56686.11 79306.56 42525.08
99 89705.83 138383.81 62832.11
100 49975.06 68330.72 38132.52
101 59484.79 83894.31 44363.38
102 52550.21 72461.05 39846.21
103 123940.57 209132.43 81900.17
104 39044.42 51386.15 30668.56
105 50374.68 68965.48 38400.67
106 59676.54 84379.75 44423.98
107 40568.37 53728.19 31711.79
108 66315.22 95530.04 48708.23
109 26455.68 33144.16 21604.97
110 51773.54 71416.50 39246.53
111 110842.52 180504.94 74915.54
112 99173.52 156726.52 68354.04
113 40119.43 53059.07 31394.72
114 43021.87 57424.24 33429.20
115 36698.50 47878.64 29021.83
116 62778.35 89669.30 46392.26
117 123994.99 209810.04 81793.06
118 53463.29 73971.07 40436.67
119 53516.45 74174.39 40424.54
120 39250.74 51693.20 30814.27
121 38078.78 49972.72 29976.05
122 101951.84 162334.22 69921.68
123 61657.16 87758.74 45679.28
124 43457.87 58225.33 33671.13
125 52096.89 71728.51 39546.39
126 81812.36 123254.53 58233.98
127 47893.80 65010.51 36744.18
128 52639.52 72753.74 39845.00
129 138041.58 241504.96 89205.91
130 90739.77 140424.79 63420.40
131 45607.12 61495.41 35166.09
132 86127.23 131979.31 60598.31
133 58032.85 81512.63 43409.63
134 65921.32 95011.66 48401.06
135 42356.24 56406.65 32969.51
136 113150.13 186052.82 76002.26
137 67714.10 98135.58 49522.41
138 57936.65 81346.37 43349.78
139 64274.61 91986.32 47431.22
140 54227.22 75215.96 40938.75
141 90304.08 139331.02 63243.70
142 39428.40 51979.68 30929.60
143 56558.51 79024.64 42470.02
144 61815.65 87818.07 45859.28
145 75520.56 112114.99 54304.94
146 56686.11 79306.56 42525.08
147 90724.23 140365.18 63420.34
148 70978.93 103830.65 51568.84
149 31041.04 39661.32 24953.68
150 186158.67 362093.43 113095.03
151 53009.90 73214.78 40146.00
152 38908.72 51172.60 30578.11
153 108299.47 175242.17 73498.98
154 38349.21 50372.13 30168.29
155 35880.83 46681.54 28436.95
156 44528.85 59754.08 34459.75
157 58944.79 82997.11 44012.91
158 33154.68 42678.62 26496.36
159 44652.54 60077.10 34486.93
160 36458.84 47535.47 28846.72
161 94111.74 147015.07 65365.61
162 93614.58 145990.53 65093.95
163 59484.79 83894.31 44363.38
164 49626.93 67773.04 37901.00
165 55856.04 77974.95 41969.43
166 47193.92 64023.09 36223.13
167 97858.64 154613.10 67458.00
168 38737.06 50923.35 30454.05
169 36093.65 46991.61 28589.84
170 44390.54 59535.71 34367.07
171 37700.26 49390.59 29717.84
172 62202.79 88449.42 46115.82
173 67301.67 97421.90 49262.41
174 58277.47 81902.79 43574.52
175 44855.58 60299.62 34665.81
176 91308.97 141381.69 63795.17
177 105982.67 170620.20 72165.30
178 107717.27 174767.18 72977.41
179 94342.40 148023.89 65334.60
180 119283.54 198681.78 79468.30
181 42623.74 56830.05 33147.76
182 52394.78 72234.13 39733.50
183 74351.68 110372.11 53466.99
184 58613.51 82453.04 43795.56
185 27648.07 34838.28 22474.16
186 35948.52 46773.09 28488.93
187 106119.82 170831.33 72261.34
188 44928.62 60438.98 34704.33
189 86127.23 131979.31 60598.31
190 77334.34 115176.71 55485.29
191 74551.56 110191.98 53772.39
192 36458.84 47535.47 28846.72
193 39250.74 51693.20 30814.27
194 96552.47 152214.58 66654.36
195 42899.32 57398.21 33273.08
196 87350.89 133684.97 61512.07
197 72213.32 105970.30 52349.26
198 116803.32 194014.66 77951.99
199 46086.84 62261.34 35484.61
200 75549.57 111997.79 54379.92
201 75805.76 112599.80 54489.33
202 51621.91 70962.68 39231.73
203 77831.18 116042.49 55799.73
204 69185.09 100689.05 50447.88
205 66315.22 95530.04 48708.23
206 50951.95 69887.77 38786.02
207 37835.93 49568.52 29824.69
208 41075.86 54506.40 32060.50
209 71604.43 104911.99 51965.19
210 79220.36 118480.52 56673.85
211 33627.90 43372.65 26833.12
212 62202.79 88449.42 46115.82
213 58370.63 82078.80 43626.69
214 95817.90 150713.71 66246.88
215 50951.95 69887.77 38786.02
216 127579.69 216646.01 83970.99
217 59702.44 84308.23 44484.64
218 82516.92 124691.05 58614.14
219 60267.43 85199.65 44869.81
220 58277.47 81902.79 43574.52
221 86462.27 132093.58 60958.70
222 42366.00 56421.00 32976.51
223 76810.41 114543.56 55060.26
224 109341.37 177382.00 74083.18
225 37835.93 49568.52 29824.69
226 97858.64 154613.10 67458.00
227 103436.77 166107.53 70546.00
228 77517.23 115455.06 55614.50
229 93964.98 147024.63 65193.01
230 52795.00 73003.97 39948.38
231 109341.37 177382.00 74083.18
232 77334.34 115176.71 55485.29
233 55272.82 77121.78 41546.62
234 42158.65 56159.01 32808.79
235 80286.73 120540.46 57283.61
236 101515.83 161479.87 69667.97
237 60267.43 85199.65 44869.81
238 54277.38 75286.37 40976.28
239 43649.15 58440.32 33837.52
240 34024.68 43951.11 27117.34
241 89612.72 138025.94 62832.56
242 55272.82 77121.78 41546.62
243 44928.62 60438.98 34704.33
244 84266.82 128471.17 59495.16
245 76294.69 113204.73 54881.67
246 82050.71 123713.05 58371.39
247 49626.93 67773.04 37901.00
248 48372.20 65925.83 36998.79
249 35781.05 46539.59 28363.64
250 105224.60 169501.07 71621.29
251 56337.02 78895.92 42232.70
252 43088.32 57530.94 33472.83
253 56337.02 78895.92 42232.70
254 64218.56 92027.69 47344.92
255 44928.62 60438.98 34704.33
256 55272.82 77121.78 41546.62
257 86025.10 131181.72 60727.14
258 88318.37 136214.89 61869.04
259 113233.17 186369.71 76011.00
260 55272.82 77121.78 41546.62
261 44928.62 60438.98 34704.33
262 56337.02 78895.92 42232.70
263 78285.32 117295.30 55934.56
264 103586.21 166194.35 70690.37
265 76294.69 113204.73 54881.67
266 81844.88 123758.90 58109.93
267 69542.68 101713.98 50530.85
268 86127.23 131979.31 60598.31
269 72618.06 107116.76 52452.09
270 35781.05 46539.59 28363.64
271 95237.70 149596.78 65905.39
272 55272.82 77121.78 41546.62
273 66012.03 95143.78 48467.17
274 55272.82 77121.78 41546.62
275 48372.20 65925.83 36998.79
276 111995.35 183673.53 75352.45
277 111995.35 183673.53 75352.45
278 56337.02 78895.92 42232.70
279 56337.02 78895.92 42232.70
280 49975.26 68511.06 38057.87
281 114648.50 189308.84 76802.92
282 44928.62 60438.98 34704.33
283 27648.07 34838.28 22474.16
284 98031.96 155026.83 67537.20
285 124398.38 210756.99 81994.90
286 56337.02 78895.92 42232.70
287 48372.20 65925.83 36998.79
288 48372.20 65925.83 36998.79
289 56337.02 78895.92 42232.70
290 111275.66 182150.88 74958.39
291 46086.84 62261.34 35484.61
292 91331.04 142075.38 63611.84
293 48372.20 65925.83 36998.79
294 74940.10 111375.60 53846.36
295 48372.20 65925.83 36998.79
296 55272.82 77121.78 41546.62
297 122383.33 206244.89 80934.93
298 69542.68 101713.98 50530.85
299 56337.02 78895.92 42232.70
300 48372.20 65925.83 36998.79
301 49975.26 68511.06 38057.87
302 48372.20 65925.83 36998.79
303 49975.26 68511.06 38057.87
304 48372.20 65925.83 36998.79
305 49975.26 68511.06 38057.87
306 55272.82 77121.78 41546.62
307 49975.26 68511.06 38057.87test3_2_dollars fit lwr upr
1 66145.66 68270.76 64118.27
2 45919.82 47674.75 44260.04
3 44897.70 45892.55 43934.86
4 46366.59 47749.66 45042.75
5 57783.36 60055.18 55638.06
6 53860.25 56326.47 51552.53
7 63380.73 65559.36 61308.92
8 50511.32 51574.49 49480.69
9 34987.91 35943.07 34070.32
10 56245.60 58392.62 54214.86
11 60322.87 63004.93 57808.49
12 41849.83 43074.96 40676.25
13 49975.06 51070.21 48914.76
14 43291.62 44644.32 41999.48
15 78777.40 83823.89 74173.29
16 44574.90 45847.05 43354.97
17 108138.96 116886.97 100337.50
18 58558.78 59689.54 57459.84
19 33627.90 34703.99 32601.09
20 58391.34 60723.83 56190.70
21 92139.96 97331.37 87353.09
22 43486.93 44580.97 42432.68
23 42132.06 43164.15 41136.55
24 26018.13 26991.69 25096.31
25 63291.41 65229.95 61438.03
26 75083.89 77737.51 72563.85
27 42390.29 43493.41 41328.61
28 51651.83 52860.00 50484.61
29 109166.29 114706.61 104017.88
30 49115.76 50131.49 48130.59
31 44547.48 46024.72 43140.25
32 52372.98 53486.55 51293.82
33 69150.75 74110.24 64672.93
34 55485.91 57544.15 53536.15
35 92450.64 96593.00 88569.15
36 92396.16 96669.31 88400.20
37 39846.85 40847.64 38882.40
38 55435.06 57734.62 53270.19
39 56686.11 58476.36 54976.83
40 45525.12 46829.55 44274.45
41 41877.97 42909.34 40883.34
42 33947.67 35071.58 32876.93
43 97561.04 101704.71 93665.54
44 36698.50 37733.18 35705.80
45 119945.79 129719.26 111236.66
46 51387.12 53501.44 49395.71
47 74363.73 77821.29 71131.57
48 31254.70 32467.07 30108.98
49 50017.16 51492.89 48603.97
50 67020.44 72472.00 62161.65
51 108668.84 118711.29 99848.83
52 64053.49 70500.46 58452.04
53 38574.96 39660.83 37533.08
54 58650.78 61052.82 56387.76
55 32870.15 33898.83 31887.60
56 57421.49 59581.03 55377.27
57 58277.47 59820.09 56793.75
58 77051.01 79857.72 74389.71
59 36394.05 37433.68 35397.13
60 137238.83 150561.27 125609.48
61 52531.85 54166.81 50969.81
62 71684.84 76503.19 67307.76
63 58367.40 61078.54 55832.85
64 44758.82 45950.79 43612.64
65 36829.29 37869.10 35831.73
66 161878.33 175726.71 149604.72
67 64367.45 66222.84 62588.96
68 51621.91 52663.46 50610.96
69 47207.74 48374.48 46082.71
70 47392.47 49690.16 45250.53
71 39251.21 40240.02 38298.40
72 60172.15 62323.64 58130.17
73 55098.13 56419.07 53823.06
74 51537.76 52565.53 50539.84
75 95349.28 103013.85 88509.36
76 90724.23 95265.68 86499.96
77 63246.89 64595.53 61940.06
78 75011.12 78179.79 72031.26
79 54993.54 57176.23 52933.50
80 79847.51 83479.64 76447.38
81 112711.37 121075.09 105185.26
82 70568.44 75521.10 66087.46
83 45478.70 47210.92 43840.10
84 32150.11 33257.17 31097.42
85 69806.96 72758.34 67031.58
86 33179.82 34398.29 32024.97
87 87954.60 92438.17 83789.50
88 35166.68 36262.14 34120.12
89 85531.70 89491.15 81829.32
90 51537.76 52565.53 50539.84
91 103915.93 110637.05 97789.17
92 47878.71 49410.19 46417.33
93 72079.29 76867.72 67724.75
94 42236.80 43350.63 41165.36
95 114174.19 123930.78 105525.98
96 65364.07 66743.61 64026.86
97 53813.43 55869.08 51869.18
98 56686.11 58476.36 54976.83
99 89705.83 94052.19 85653.94
100 49975.06 51070.21 48914.76
101 59484.79 60870.46 58145.91
102 52550.21 53608.08 51523.34
103 123940.57 133260.44 115565.29
104 39044.42 40102.86 38027.34
105 50374.68 51440.72 49341.44
106 59676.54 62109.54 57383.75
107 40568.37 41881.06 39316.45
108 66315.22 68040.00 64655.20
109 26455.68 27430.55 25531.86
110 51773.54 54091.29 49601.62
111 110842.52 116345.13 105721.25
112 99173.52 103538.17 95079.14
113 40119.43 41489.63 38816.00
114 43021.87 43999.82 42076.16
115 36698.50 37733.18 35705.80
116 62778.35 65580.86 60151.71
117 123994.99 135028.21 114260.82
118 53463.29 54791.04 52183.23
119 53516.45 55576.39 51568.96
120 39250.74 40286.31 38254.60
121 38078.78 39342.20 36875.26
122 101951.84 106792.80 97432.73
123 61657.16 64376.34 59106.70
124 43457.87 45212.49 41803.43
125 52096.89 53147.11 51077.50
126 81812.36 84150.33 79570.48
127 47893.80 48826.08 46987.98
128 52639.52 54685.72 50706.05
129 138041.58 151005.07 126678.49
130 90739.77 95415.63 86399.38
131 45607.12 47061.46 44219.17
132 86127.23 91837.37 80933.56
133 58032.85 59690.23 56443.56
134 65921.32 68635.48 63365.02
135 42356.24 43366.79 41380.60
136 113150.13 121630.34 105526.85
137 67714.10 70587.24 65012.87
138 57936.65 59546.19 56391.50
139 64274.61 65645.51 62946.20
140 54227.22 55578.15 52924.96
141 90304.08 93647.09 87136.94
142 39428.40 40586.96 38318.74
143 56558.51 57821.50 55336.46
144 61815.65 63269.70 60411.16
145 75520.56 79456.80 71869.73
146 56686.11 58476.36 54976.83
147 90724.23 95265.68 86499.96
148 70978.93 73844.34 68277.11
149 31041.04 32233.69 29913.37
150 186158.67 205874.90 169144.82
151 53009.90 54160.29 51895.78
152 38908.72 39901.68 37952.38
153 108299.47 113597.05 103364.01
154 38349.21 39584.68 37170.69
155 35880.83 36992.19 34818.82
156 44528.85 45530.43 43559.96
157 58944.79 60362.74 57576.21
158 33154.68 34197.68 32158.69
159 44652.54 46447.54 42959.61
160 36458.84 37566.79 35399.19
161 94111.74 99287.76 89330.17
162 93614.58 98513.67 89072.05
163 59484.79 60870.46 58145.91
164 49626.93 50696.74 48590.63
165 55856.04 57842.07 53970.58
166 47193.92 48909.34 45567.20
167 97858.64 104234.45 92050.42
168 38737.06 39788.67 37726.60
169 36093.65 37180.45 35053.80
170 44390.54 45358.68 43453.07
171 37700.26 38867.31 36585.00
172 62202.79 63443.15 60998.45
173 67301.67 70174.47 64601.74
174 58277.47 59820.09 56793.75
175 44855.58 46139.52 43624.50
176 91308.97 95368.69 87503.07
177 105982.67 111681.66 100709.02
178 107717.27 115759.31 100485.06
179 94342.40 101549.73 87875.99
180 119283.54 126909.77 112324.62
181 42623.74 43732.32 41556.78
182 52394.78 53662.19 51171.75
183 74351.68 79557.03 69640.98
184 58613.51 60092.04 57188.90
185 27648.07 28756.56 26602.46
186 35948.52 37010.69 34931.42
187 106119.82 111522.98 101100.01
188 44928.62 46374.09 43549.71
189 86127.23 91837.37 80933.56
190 77334.34 80293.81 74535.54
191 74551.56 77588.01 71689.93
192 36458.84 37566.79 35399.19
193 39250.74 40286.31 38254.60
194 96552.47 103460.23 90314.11
195 42899.32 44792.11 41124.02
196 87350.89 90407.94 84446.31
197 72213.32 74877.30 69689.03
198 116803.32 126354.70 108295.39
199 46086.84 47644.91 44603.96
200 75549.57 78692.68 72591.07
201 75805.76 79628.87 72251.50
202 51621.91 52663.46 50610.96
203 77831.18 80596.40 75205.86
204 69185.09 72044.30 66492.77
205 66315.22 68040.00 64655.20
206 50951.95 52002.12 49933.27
207 37835.93 38850.24 36860.83
208 41075.86 42434.02 39781.88
209 71604.43 74362.72 68996.81
210 79220.36 81394.80 77131.90
211 33627.90 34703.99 32601.09
212 62202.79 63443.15 60998.45
213 58370.63 60066.41 56745.66
214 95817.90 102478.97 89785.78
215 50951.95 52002.12 49933.27
216 127579.69 135499.64 120334.37
217 59702.44 61468.26 58011.62
218 82516.92 85728.86 79482.16
219 60267.43 61611.68 58966.70
220 58277.47 59820.09 56793.75
221 86462.27 89984.51 83142.86
222 42366.00 43371.80 41394.79
223 76810.41 81212.27 72756.98
224 109341.37 114674.08 104372.18
225 37835.93 38850.24 36860.83
226 97858.64 104234.45 92050.42
227 103436.77 111368.39 96323.26
228 77517.23 80165.28 74998.25
229 93964.98 100265.02 88240.59
230 52795.00 54837.41 50864.61
231 109341.37 114674.08 104372.18
232 77334.34 80293.81 74535.54
233 55272.82 57770.10 52934.04
234 42158.65 43528.90 40852.09
235 80286.73 83210.21 77514.66
236 101515.83 106425.74 96938.02
237 60267.43 61611.68 58966.70
238 54277.38 55536.66 53060.45
239 43649.15 44977.19 42379.08
240 34024.68 35101.10 32997.02
241 89612.72 93023.59 86386.07
242 55272.82 57770.10 52934.04
243 44928.62 46374.09 43549.71
244 84266.82 89815.92 79216.54
245 76294.69 78657.08 74037.15
246 82050.71 84526.69 79681.96
247 49626.93 50696.74 48590.63
248 48372.20 50331.79 46524.86
249 35781.05 36922.17 34692.03
250 105224.60 112512.23 98622.76
251 56337.02 58977.39 53870.08
252 43088.32 44102.01 42109.17
253 56337.02 58977.39 53870.08
254 64218.56 66560.85 61997.77
255 44928.62 46374.09 43549.71
256 55272.82 57770.10 52934.04
257 86025.10 89012.88 83185.27
258 88318.37 94459.73 82757.04
259 113233.17 122177.51 105236.24
260 55272.82 57770.10 52934.04
261 44928.62 46374.09 43549.71
262 56337.02 58977.39 53870.08
263 78285.32 83035.94 73931.03
264 103586.21 110814.20 97043.01
265 76294.69 78657.08 74037.15
266 81844.88 86487.34 77566.42
267 69542.68 74063.57 65423.44
268 86127.23 91837.37 80933.56
269 72618.06 77184.35 68445.32
270 35781.05 36922.17 34692.03
271 95237.70 101927.41 89185.61
272 55272.82 57770.10 52934.04
273 66012.03 68601.32 63566.62
274 55272.82 57770.10 52934.04
275 48372.20 50331.79 46524.86
276 111995.35 120507.89 104353.93
277 111995.35 120507.89 104353.93
278 56337.02 58977.39 53870.08
279 56337.02 58977.39 53870.08
280 49975.26 52147.46 47936.01
281 114648.50 123583.74 106648.40
282 44928.62 46374.09 43549.71
283 27648.07 28756.56 26602.46
284 98031.96 104673.56 92002.99
285 124398.38 135652.59 114488.75
286 56337.02 58977.39 53870.08
287 48372.20 50331.79 46524.86
288 48372.20 50331.79 46524.86
289 56337.02 58977.39 53870.08
290 111275.66 119661.95 103741.04
291 46086.84 47644.91 44603.96
292 91331.04 97975.70 85340.11
293 48372.20 50331.79 46524.86
294 74940.10 80000.55 70345.04
295 48372.20 50331.79 46524.86
296 55272.82 57770.10 52934.04
297 122383.33 133116.23 112898.03
298 69542.68 74063.57 65423.44
299 56337.02 58977.39 53870.08
300 48372.20 50331.79 46524.86
301 49975.26 52147.46 47936.01
302 48372.20 50331.79 46524.86
303 49975.26 52147.46 47936.01
304 48372.20 50331.79 46524.86
305 49975.26 52147.46 47936.01
306 55272.82 57770.10 52934.04
307 49975.26 52147.46 47936.01test2_2_dollarsnew = data.frame(Name = ecars$Car_name,
Make = ecars$Make,
Price = ecars$Price/1000,
Predicted_price = (test2_2_dollars[,1]/1000),
Predicted_price_lwr = (test2_2_dollars[,2]/1000),
Predicted_price_upr = (test2_2_dollars[,3]/1000),
Confidence_price_lwr = (test3_2_dollars[,2]/1000),
Confidence_price_upr = (test3_2_dollars[,3])/1000)
test2_2_dollarsnew# cars groups by brands with the most models
most_makes = test2_2_dollarsnew %>% group_by(Make) %>%
filter(n() >= 10) %>%
summarise(average_cost = (mean(Price)), average_predicted_cost = (mean(Predicted_price)))
gplt1 = ggplot(NULL, aes(Predicted_price, Price)) +
geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Predicted_price)) +
geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Predicted_price_lwr), col = 'red') +
geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Predicted_price_upr), col = 'red') +
geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Confidence_price_lwr), col = 'blue') +
geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Confidence_price_upr), col = 'blue') +
ylim(0,250)+
geom_point(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Price), alpha = .5) +
geom_point(data = most_makes, aes(x = average_predicted_cost, y = average_cost), size = 3, shape = 23, fill = make_colors) +
scale_color_manual(values = make_colors)
ecarsplot_ly(
data = ecars_make,
x = ~Price,
type = "box",
text = ~Car_name,
tooltip = c("x", "text")
)Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'plot_ly(
data = ecars_make,
x = ~Price,
y = ~Make,
type = "box",
color = ~Make,
colors = make_colors,
text = ~Car_name,
tooltip = c("x", "text"),
showlegend = FALSE
)Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
Warning: 'box' objects don't have these attributes: 'tooltip'
Valid attributes include:
'alignmentgroup', 'boxmean', 'boxpoints', 'customdata', 'customdatasrc', 'dx', 'dy', 'fillcolor', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hoveron', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'jitter', 'legendgroup', 'legendgrouptitle', 'legendrank', 'line', 'lowerfence', 'lowerfencesrc', 'marker', 'mean', 'meansrc', 'median', 'mediansrc', 'meta', 'metasrc', 'name', 'notched', 'notchspan', 'notchspansrc', 'notchwidth', 'offsetgroup', 'opacity', 'orientation', 'pointpos', 'q1', 'q1src', 'q3', 'q3src', 'quartilemethod', 'sd', 'sdsrc', 'selected', 'selectedpoints', 'showlegend', 'stream', 'text', 'textsrc', 'transforms', 'type', 'uid', 'uirevision', 'unselected', 'upperfence', 'upperfencesrc', 'visible', 'whiskerwidth', 'width', 'x', 'x0', 'xaxis', 'xcalendar', 'xhoverformat', 'xperiod', 'xperiod0', 'xperiodalignment', 'xsrc', 'y', 'y0', 'yaxis', 'ycalendar', 'yhoverformat', 'yperiod', 'yperiod0', 'yperiodalignment', 'ysrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'options(repr.plot.width = 15, repr.plot.height =2)
ggplot(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Price)) +
geom_point() +
geom_line(aes(x = Predicted_price, y = Predicted_price)) +
geom_line(aes(x = Predicted_price, y = Predicted_price_lwr), col = 'red') +
geom_line(aes(x = Predicted_price, y = Predicted_price_upr)) +
geom_line(aes(x = Predicted_price, y = Confidence_price_lwr)) +
geom_line(aes(x = Predicted_price, y = Confidence_price_upr)) #+
geom_point(aes(x = most_makes$average_cost, y =most_makes$average_predicted_cost))mapping: x = ~most_makes$average_cost, y = ~most_makes$average_predicted_cost
geom_point: na.rm = FALSE
stat_identity: na.rm = FALSE
position_identity
newfunction (Class, ...)
{
ClassDef <- getClass(Class, where = topenv(parent.frame()))
value <- .Call(C_new_object, ClassDef)
initialize(value, ...)
}
<bytecode: 0x0000021c472546e8>
<environment: namespace:methods>newfunction (Class, ...)
{
ClassDef <- getClass(Class, where = topenv(parent.frame()))
value <- .Call(C_new_object, ClassDef)
initialize(value, ...)
}
<bytecode: 0x0000021c472546e8>
<environment: namespace:methods>new %>% group_by(Make) %>%
filter(n() >= 10) %>%
summarise(average_cost = (mean(Price)/1000), average_predicted_cost = (mean(Predicted_price)/1000)) #%>%Error in UseMethod("group_by") :
no applicable method for 'group_by' applied to an object of class "function"new %>% group_by(Make) %>%
filter(n() >= 10) %>%
summarise(average_price = (mean(Price)/1000), average_predicted_price = (mean(Predicted_price)/1000))%>%
ggplot(., aes(x = average_predicted_price, y = average_price)) +
geom_point(aes(color = Make), size =4) Error in UseMethod("group_by") :
no applicable method for 'group_by' applied to an object of class "function"new
new %>% group_by(Make) %>%
filter(n() >= 10) %>%
summarise(average_price = (mean(Price)/1000), average_predicted_price = (mean(Predicted_price)/1000))%>%
ggplot(., aes(x = average_predicted_price, y = average_price)) +
geom_point(aes(color = Make), size =4) +
geom_line(aes(x = average_predicted_price, y = average_predicted_price)) +
predict(model, newdata, interval = 'confidence')
predict(model, newdata, interval = 'prediction')new
new %>% group_by(Make) %>%
filter(n() >= 10) %>%
summarise(average_price = (mean(Price)/1000), average_predicted_price = (mean(Predicted_price)/1000))ecars_missing_price
premodelecarsmodel.empty = lm(Price_pow ~ 1, data = ecars)
model.full = lm(Price_pow ~ Efficiency_pow + Range + Battery + Speed_pow + Fast_charge + Acceleration, data = ecars)
scope = list(lower = formula(model.empty), upper = formula(model.full))
scope$lower
Price_pow ~ 1
$upper
Price_pow ~ Efficiency_pow + Range + Battery + Speed_pow + Fast_charge +
AccelerationforwardAIC = step(model.empty, scope, direction = 'forward', k = 2)Start: AIC=-4363.96
Price_pow ~ 1
Df Sum of Sq RSS AIC
+ Battery 1 1.3640e-04 6.8190e-05 -4699.3
+ Speed_pow 1 1.0767e-04 9.6914e-05 -4591.3
+ Range 1 8.6310e-05 1.1828e-04 -4530.2
+ Fast_charge 1 8.0946e-05 1.2364e-04 -4516.6
+ Acceleration 1 6.0434e-05 1.4415e-04 -4469.4
+ Efficiency_pow 1 2.1897e-05 1.8269e-04 -4396.7
<none> 2.0459e-04 -4364.0
Step: AIC=-4699.26
Price_pow ~ Battery
Df Sum of Sq RSS AIC
+ Speed_pow 1 8.4306e-06 5.9759e-05 -4737.8
+ Fast_charge 1 6.8139e-06 6.1376e-05 -4729.6
+ Efficiency_pow 1 6.6610e-06 6.1529e-05 -4728.8
+ Range 1 3.8502e-06 6.4339e-05 -4715.1
+ Acceleration 1 7.4760e-07 6.7442e-05 -4700.6
<none> 6.8190e-05 -4699.3
Step: AIC=-4737.78
Price_pow ~ Battery + Speed_pow
Df Sum of Sq RSS AIC
+ Efficiency_pow 1 2.1733e-05 3.8026e-05 -4874.6
+ Range 1 1.4127e-05 4.5632e-05 -4818.6
+ Acceleration 1 5.0183e-06 5.4741e-05 -4762.7
+ Fast_charge 1 8.4290e-07 5.8916e-05 -4740.1
<none> 5.9759e-05 -4737.8
Step: AIC=-4874.56
Price_pow ~ Battery + Speed_pow + Efficiency_pow
Df Sum of Sq RSS AIC
+ Fast_charge 1 4.157e-06 3.3869e-05 -4908.1
+ Range 1 3.319e-06 3.4707e-05 -4900.6
<none> 3.8026e-05 -4874.6
+ Acceleration 1 1.310e-08 3.8013e-05 -4872.7
Step: AIC=-4908.1
Price_pow ~ Battery + Speed_pow + Efficiency_pow + Fast_charge
Df Sum of Sq RSS AIC
+ Range 1 1.777e-06 3.2092e-05 -4922.6
<none> 3.3869e-05 -4908.1
+ Acceleration 1 3.125e-08 3.3838e-05 -4906.4
Step: AIC=-4922.64
Price_pow ~ Battery + Speed_pow + Efficiency_pow + Fast_charge +
Range
Df Sum of Sq RSS AIC
<none> 3.2092e-05 -4922.6
+ Acceleration 1 9.5837e-08 3.1996e-05 -4921.6battery speed_pow efficiency and fast charge
forwardAIC2 = step(model.empty2, scope2, direction = 'forward', k = 2)
Start: AIC=6415.84
Price ~ 1
Df Sum of Sq RSS AIC
+ Top_speed 1 2.1023e+11 1.5319e+11 6152.6
+ Battery 1 1.7911e+11 1.8431e+11 6209.4
+ Fast_charge 1 1.3923e+11 2.2419e+11 6269.5
+ Range 1 1.2615e+11 2.3728e+11 6287.0
+ Acceleration 1 1.0296e+11 2.6046e+11 6315.6
+ Efficiency 1 1.1067e+10 3.5235e+11 6408.3
<none> 3.6342e+11 6415.8
Step: AIC=6152.62
Price ~ Top_speed
Df Sum of Sq RSS AIC
+ Efficiency 1 4.2802e+10 1.1039e+11 6054.0
+ Battery 1 1.9965e+10 1.3322e+11 6111.8
+ Acceleration 1 1.5065e+10 1.3812e+11 6122.8
<none> 1.5319e+11 6152.6
+ Fast_charge 1 2.2387e+08 1.5297e+11 6154.2
+ Range 1 7.0491e+07 1.5312e+11 6154.5
Step: AIC=6054.03
Price ~ Top_speed + Efficiency
Df Sum of Sq RSS AIC
+ Fast_charge 1 3519695484 1.0687e+11 6046.1
+ Range 1 3506122724 1.0688e+11 6046.1
+ Battery 1 3063673448 1.0732e+11 6047.4
+ Acceleration 1 915987463 1.0947e+11 6053.5
<none> 1.1039e+11 6054.0
Step: AIC=6046.08
Price ~ Top_speed + Efficiency + Fast_charge
Df Sum of Sq RSS AIC
+ Range 1 2137906570 1.0473e+11 6041.9
+ Battery 1 2032210165 1.0484e+11 6042.2
+ Acceleration 1 713779942 1.0615e+11 6046.0
<none> 1.0687e+11 6046.1
Step: AIC=6041.87
Price ~ Top_speed + Efficiency + Fast_charge + Range
Df Sum of Sq RSS AIC
+ Acceleration 1 1639080066 1.0309e+11 6039.0
<none> 1.0473e+11 6041.9
+ Battery 1 1076868 1.0473e+11 6043.9
Step: AIC=6039.03
Price ~ Top_speed + Efficiency + Fast_charge + Range + Acceleration
Df Sum of Sq RSS AIC
<none> 1.0309e+11 6039.0
+ Battery 1 1.37e+08 1.0295e+11 6040.6forwardAIC3 = step(model.empty3, scope3, direction = 'forward', k = 2)
Start: AIC=-4363.96
Price_pow ~ 1
Df Sum of Sq RSS AIC
+ Battery 1 1.3640e-04 6.8190e-05 -4699.3
+ Top_speed 1 1.1336e-04 9.1232e-05 -4609.9
+ Range 1 8.6310e-05 1.1828e-04 -4530.2
+ Fast_charge 1 8.0946e-05 1.2364e-04 -4516.6
+ Acceleration 1 6.0434e-05 1.4415e-04 -4469.4
+ Efficiency 1 1.9016e-05 1.8557e-04 -4391.9
<none> 2.0459e-04 -4364.0
Step: AIC=-4699.26
Price_pow ~ Battery
Df Sum of Sq RSS AIC
+ Top_speed 1 1.1639e-05 5.6551e-05 -4754.7
+ Fast_charge 1 6.8139e-06 6.1376e-05 -4729.6
+ Efficiency 1 6.4609e-06 6.1729e-05 -4727.8
+ Range 1 3.8502e-06 6.4339e-05 -4715.1
+ Acceleration 1 7.4760e-07 6.7442e-05 -4700.6
<none> 6.8190e-05 -4699.3
Step: AIC=-4754.72
Price_pow ~ Battery + Top_speed
Df Sum of Sq RSS AIC
+ Efficiency 1 2.1501e-05 3.5050e-05 -4899.6
+ Range 1 1.4243e-05 4.2308e-05 -4841.8
+ Acceleration 1 5.9843e-06 5.0567e-05 -4787.1
<none> 5.6551e-05 -4754.7
+ Fast_charge 1 2.2690e-07 5.6324e-05 -4753.9
Step: AIC=-4899.57
Price_pow ~ Battery + Top_speed + Efficiency
Df Sum of Sq RSS AIC
+ Fast_charge 1 3.1856e-06 3.1865e-05 -4926.8
+ Range 1 2.5096e-06 3.2541e-05 -4920.4
<none> 3.5050e-05 -4899.6
+ Acceleration 1 1.2000e-09 3.5049e-05 -4897.6
Step: AIC=-4926.83
Price_pow ~ Battery + Top_speed + Efficiency + Fast_charge
Df Sum of Sq RSS AIC
+ Range 1 1.3707e-06 3.0494e-05 -4938.3
<none> 3.1865e-05 -4926.8
+ Acceleration 1 6.7350e-08 3.1797e-05 -4925.5
Step: AIC=-4938.32
Price_pow ~ Battery + Top_speed + Efficiency + Fast_charge +
Range
Df Sum of Sq RSS AIC
+ Acceleration 1 2.3039e-07 3.0263e-05 -4938.7
<none> 3.0494e-05 -4938.3
Step: AIC=-4938.65
Price_pow ~ Battery + Top_speed + Efficiency + Fast_charge +
Range + AccelerationI’m getting a lower AIC when I run these without transforming them??? I need to transform price but not the others?? not sure what to do??
model.empty = lm(Price_pow ~ 1, data = ecars)
model.full = lm(Price_pow ~ Efficiency_pow + Range + Battery + Speed_pow + Fast_charge + Acceleration, data = ecars)
scope = list(lower = formula(model.empty), upper = formula(model.full))
scope
forwardAIC = step(model.empty, scope, direction = 'forward', k = 2)summary(model_box)
Call:
lm(formula = Price ~ Top_speed + Range + Efficiency + Fast_charge +
Acceleration, data = ecars)
Residuals:
Min 1Q Median 3Q Max
-53655 -11767 -328 8350 82937
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.731e+05 1.497e+04 -11.561 < 2e-16 ***
Top_speed 7.047e+02 7.058e+01 9.984 < 2e-16 ***
Range 4.992e+01 1.669e+01 2.991 0.00301 **
Efficiency 3.730e+02 3.831e+01 9.736 < 2e-16 ***
Fast_charge 1.699e+01 7.692e+00 2.208 0.02797 *
Acceleration 1.637e+03 7.485e+02 2.188 0.02947 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 18510 on 301 degrees of freedom
Multiple R-squared: 0.7163, Adjusted R-squared: 0.7116
F-statistic: 152 on 5 and 301 DF, p-value: < 2.2e-16lambda
[1] -0.7070707****This is how to undo the lambda transformation
ecars$Price
[1] 59017 46220 44625 39990 55220 47567 77300 41790 23300
[10] 53668 59200 46600 55000 42900 63667 45690 110970 67300
[19] 34990 70805 95970 35990 39370 22550 70200 70800 41990
[28] 37990 139900 47490 36590 42490 51990 56995 100100 85300
[37] 34990 47578 48900 47190 39995 36840 76490 39100 146050
[46] 46450 71400 35700 56500 61100 72990 54000 37000 58990
[55] 33400 64581 46335 63970 36040 218000 45990 47900 47567
[64] 47590 29990 95990 54475 48490 47900 43900 40650 46990
[73] 48990 57490 109551 69950 53000 60970 51150 99500 106050
[82] 55980 38490 35990 68990 36400 57000 37840 72490 68000
[91] 100970 53514 59200 44765 115970 59950 43900 48970 87550
[100] 56500 52950 50470 136100 36490 43490 46990 41100 58775
[109] 24550 47595 135434 82380 47000 44200 37540 58500 159000
[118] 47500 50775 40050 38990 88600 50990 33990 57390 74400
[127] 47490 46990 218000 105550 50777 71626 81900 65900 40335
[136] 89790 68500 51150 61400 41560 99841 36900 55800 54450
[145] 92400 63300 69950 67187 39900 150990 50990 45765 110801
[154] 32740 38045 40490 49020 42000 37490 41540 129000 110650
[163] 53255 56424 53400 52205 141705 39300 36775 39563 41990
[172] 59000 90900 54950 46950 115700 95800 139906 98863 181800
[181] 43490 47500 109000 56455 30990 34650 95200 37790 64248
[190] 61990 74500 41540 40540 113359 35490 86811 74149 197740
[199] 42440 94900 77300 45970 68970 68500 65275 55519 39990
[208] 44490 70995 76650 36990 54950 59500 67300 58197 155009
[217] 59500 89548 61000 61050 69200 40750 93139 124545 49445
[226] 125378 120081 88215 103254 53090 114609 71490 56942 49490
[235] 83479 98050 56950 46490 37800 37990 124920 64530 40150
[244] 114559 52990 104756 53520 53640 37990 139438 70075 47588
[253] 65385 65500 43050 57940 110706 65140 164420 57940 41240
[262] 60430 63200 119914 58890 94091 68056 72519 60678 40990
[271] 73100 59640 85900 59640 53640 140858 165848 58730 62990
[280] 54430 199168 43640 35490 99815 198692 60430 51940 63250
[289] 58730 120081 44750 114559 51940 61571 54430 61990 165372
[298] 68949 57775 50992 64075 52730 52730 55990 51825 69250
[307] 56990plot.new()
plot( x = 50, y = 54)
lines(predicted_price$Predicted, predicted_price$Predicted)
This is an R Markdown Notebook. When you execute code within the notebook, the results appear beneath the code.
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---
title: "R Notebook"
output: html_notebook
---
About this file
Data Fields:

- Battery: The capacity of the vehicle's battery in kilowatt-hours (kWh).

- Car_name: The model name of the electric vehicle.

- Car_name_link: A direct link to the corresponding page on EV Database for more in-depth information.

- Efficiency: The energy efficiency rating of the vehicle in watt-hours per kilometer (Wh/km).

- Fast_charge: The fast-charging capability of the vehicle in minutes for a certain charging percentage.

- Price.DE.:The price of the electric vehicle in Germany.

- Range: The driving range of the vehicle on a single charge in kilometers.

- Top_speed:The maximum speed the vehicle can achieve in kilometers per hour.

- Acceleration..0.100.: The acceleration time from 0 to 100 kilometers per hour.
```{r}
library(dplyr)
library(ggplot2)
library(tidyr)
library(car)
library(MASS)
library(repr)
install.packages('pals')
library(pals)
install.packages('broom')
```


```{r}
ecars_raw = read.csv('EV_cars.csv')
ecars_raw

```

```{r}
#rename some of the columns
ecars_raw = ecars_raw %>% rename(Price = Price.DE., Acceleration = acceleration..0.100.)
```

```{r}

# extract the Make of each car into its own column
make = strsplit(ecars_raw$Car_name, split = ' ')

make_ = c()
n = length(make)

for (i in 1:n) {
  make_[i] = make[[i]][1]
}

ecars_raw$Make = make_
```

```{r}
# move columns so continuous variables are together 
ecars_raw = ecars_raw %>% relocate(Make, .before = Car_name_link)
ecars_raw = ecars_raw %>% relocate(Battery, .after = Car_name_link)
ecars_raw
```
```{r}
ecars_raw = ecars_raw %>% filter(!is.na(Fast_charge))
ecars = ecars_raw %>% filter(!is.na(Price))
ecars_missing_price = ecars_raw %>% filter(is.na(Price))
```

This data required minimal processing. I created a Make variable by extracting the first word from the Car_name variable. I also renamed several columns to make them more intuitive for example acceleration..0.100. to Acceleration. I removed the two cars that did not have Fast Charge (the Renault Twingo Electric and the e.Go e.wave X) capability because this was an important feature in the linear regression and was impacting their price. Finally I made sure all the continuous variables were next to each other to simplify calling them. I split the dataframe into two. One with prices(307 objects) and one with missing prices (51 objects). 

After cleaning the data 45 unique car makes were included in the ecars data used to create the linear model and 22 unique car makes were included in the data with missing prices. Additionally 14 makes that have 10 or more car models are highlighted throughout the project.  

```{r}
length(ecars$Price)
```
```{r}
ecars
library(tibble)

ggplot(ecars, aes(Price, y = factor(0))) +
  geom_boxplot()+
  theme(axis.title.y=element_blank(),axis.text.y=element_blank(),axis.ticks.y=element_blank())



```
```{r}
Noecars = ecars

Noecars$Make2 = Noecars$Make
Noecars
makes = most_makes$Make
makes
Noecars$Make3 = ifelse(Noecars$Make2 %in% makes, Noecars$Make2, "Other")
Noecars$Make2 %in% makes
Noecars
```

```{r}
ecars_make

is_outlier <- function(x) {
  return(x < quantile(x, 0.25) - 1.5 * IQR(x) | x > quantile(x, 0.75) + 1.5 * IQR(x))
}

dat <- ecars %>% tibble::rownames_to_column(var="outlier") %>%
  mutate(is_outlier=ifelse(is_outlier(Price), Price, as.numeric(NA)))

dat
dat$outlier[which(is.na(dat$is_outlier))] <- as.numeric(NA)

ggplot(dat, aes(y=Price, x=factor(0))) + geom_boxplot() + geom_text(aes(label=outlier),na.rm=TRUE,nudge_y=0.1)

ggplot(ecars_make, aes(Top_speed, Make, fill = Make)) +
   scale_fill_manual(values = make_colors)+
  geom_boxplot(outlier.colour="black", outlier.shape=16, outlier.size=2, notch=FALSE)
```

```{r}
ecars %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  summarise(average_cost = (mean(Price)/1000)) %>%
  ggplot(., aes(x = Make, y = average_cost, fill = Make, label = Make)) +
  geom_bar(stat = 'identity') +
  scale_fill_manual(values = make_colors) +
  ylab('Average cost in Germany in 100s of eruros')+
  theme(axis.title.x=element_blank(),
        axis.text.x=element_blank(),
        axis.ticks.x=element_blank()) +
  geom_text(angle = 90, position = position_stack(vjust = 0.5)) + 
  theme(legend.position = "none")
```
```{r}
ecars
```

```{r}
top_10 = ecars %>% group_by(Make) %>%
  filter(n() >= 10) #%>%
  #summarise(average_cost = mean(Price))
top_10



make_colors = c('#e6194b', '#f58231',  '#ffe119', 
                '#bcf60c','#3cb44b', '#008080',
                '#aaffc3', '#4363d8', '#000075',
                '#46f0f0', '#911eb4', '#e6beff',
                '#f032e6', '#fabebe')


ecars %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  ggplot(., aes(x = Battery, y = Price)) +
  geom_point(aes(col = Make), size = 2) + 
  scale_color_manual(values = make_colors)


ecars %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  ggplot(., aes(x = Efficiency, y = Price)) +
  geom_point(aes(col = Make)) 

efficiency_make = ecars %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  ggplot(., aes(x = Efficiency, y = Price)) +
  geom_point(aes(col = Make), show.legend = FALSE) +
  facet_wrap(~Make)+
  scale_color_manual(values = make_colors)

efficiency_make

battery_make = ecars %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  ggplot(., aes(x = Battery, y = Price)) +
  geom_point(aes(col = Make), show.legend = FALSE) +
  facet_wrap(~Make)
battery_make
#ggsave('battery_make.png', width = 15, height = 9)

#ggsave('efficiency_make.png', width = 15, height = 9)

#keep working on this'
battery_price = ggplot(NULL, aes(x = 'Battery', y = Price)) +
  geom_point(data = ecars, aes(x = Battery, y = Price)) +
  geom_point(data = top_10, aes(x = Battery, y = Price, col = Make))# + scale_color_manual(values = make_colors)#

battery_price
ggsave('battery_price.png', width = 10)

#ecars %>% group_by(Make)%>%
 # summarise(average_cost = mean(Price)) %>%
  #arrange(average_cost)
```
```{r}
ecars %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  ggplot(., aes(x = Battery, y = Price)) +
  geom_point(aes(col = Make), show.legend = FALSE) 

BatvPrice = ggplot(NULL, aes(x = Battery, y = Price)) +
  geom_point(data = ecars, aes(x = Battery, y = Price, fill = 'black')) +
  geom_point(data = top_10, aes(x = Battery, y = Price, col = Make)) + 
  scale_color_manual(values = make_colors)+
  xlab("Battery Capacity (kWh)") + 
  ylab("Price in Germany (euros) ") +
  ggtitle('Electric Vehicle Battery vs. Price (makes with 10+ Models Highlighted)') +
  labs(fill="") +
  scale_fill_discrete(labels=c('Other')) +
  theme(legend.position = "bottom")

BatvPrice

ggsave('BatvPrice.png', width = 10)

ecars
```
```{r}
ggarrange(a, b, c, d, 
          labels = c("A", "B", "C", "D"),
          ncol = 2, nrow = 2)
```


```{r}
BatvRange = ggplot(NULL, aes(x = Battery, y = Range)) +
  geom_point(data = ecars, aes(x = Battery, y = Range, fill = 'black')) +
  geom_point(data = top_10, aes(x = Battery, y = Range, col = Make)) + 
  scale_color_manual(values = make_colors)+
  xlab("Battery Capacity (kWh)") + 
  ylab("Range (km on one charge) ") +
  ggtitle('Electric Vehicle Battery vs. Range (makes with 10+ Models Highlighted)') +
  labs(fill="") +
  scale_fill_discrete(labels=c('Other')) +
  theme(legend.position = "bottom")


AccvPrice = ggplot(NULL, aes(x = Acceleration, y = Price)) +
  geom_point(data = ecars, aes(x = Acceleration, y = Price, fill = 'black')) +
  geom_point(data = top_10, aes(x = Acceleration, y = Price, col = Make)) + 
  scale_color_manual(values = make_colors)+
  xlab("Acceleration (seconds to 100 km/hr)") + 
  ylab("Price in Germany (euros) ") +
  ggtitle('Acceleration vs. Price (makes with 10+ Models Highlighted)') +
  labs(fill="") +
  xlim(2,15)+
  scale_fill_discrete(labels=c('Other')) +
  theme(legend.position = "bottom")

BatvRange
BatvPrice
AccvPrice
```




```{r}
unique(ecars$Make)
unique(ecars_missing_price$Make)

length(unique(ecars$Make))
length(unique(ecars_missing_price$Make))

ecars_missing_price
```

```{r}
ecars
plot(ecars[,4:10], main = 'Comparison of all Quantitive Features')
plot(ecars$Acceleration, ecars$Battery)

ecars$Price_pow = (ecars$Price ** -.5)
ecars$Speed_pow = (ecars$Top_speed ** .25)
ecars$Efficiency_pow = (ecars$Efficiency ** .25)
summary(ecars)
sapply(ecars, sd)
hist(ecars$Price) 
hist(ecars$Price_pow) 
hist(ecars$Efficiency)
hist(ecars$Price_pow)
ecars
```
Colinearity with predicting Range based n battery

```{r}
ecars %>% group_by(Make) %>%
  filter(n() >= 10) %>%o
  ggplot(., aes(x = Battery, y = Price)) +
  
```

```{r}

RBmodel = lm(Range ~  Battery, data = ecars)
summary(RBmodel)
plot(RBmodel) 

PBmodel = lm(Price ~  Battery, data = ecars)
summary(PBmodel)
plot(PBmodel) 

ATmodel = lm(Top_speed ~ Acceleration, data = ecars)
summary(ATmodel)
plot(ATmodel)

model = lm(Price_pow ~ Efficiency_pow + Range + Speed_pow + Fast_charge, data = ecars)
summary(model) 
plot(model)

#battery speed_pow efficiency and fast charge 

```
With transformation done to price 
```{r}
ecars_missing_price$Speed_pow = (ecars_missing_price$Top_speed ** .25)
ecars_missing_price$Efficiency_pow = (ecars_missing_price$Efficiency ** .25)
test = predict(model, ecars_missing_price, interval = 'prediction')
test_2_dollars = (1/(test))^2
ecars_missing_price
test_2_dollars
ecars_missing_price$predicted_price = (test_2_dollars[,1])
ecars_missing_price
```
```{r}
test2 = predict(model, ecars, interval = 'prediction')
test3 = predict(model, ecars, interval = 'confidence')
test2_2_dollars = (1/(test2))^2
test3_2_dollars = (1/(test3))^2
test2_2_dollars
test3_2_dollars
test2_2_dollarsnew = data.frame(Name = ecars$Car_name,
                 Make = ecars$Make,
                 Price = ecars$Price/1000, 
                 Predicted_price = (test2_2_dollars[,1]/1000),
                 Predicted_price_lwr = (test2_2_dollars[,2]/1000),
                 Predicted_price_upr = (test2_2_dollars[,3]/1000),
                 Confidence_price_lwr = (test3_2_dollars[,2]/1000),
                 Confidence_price_upr = (test3_2_dollars[,3])/1000)
test2_2_dollarsnew
```
```{r}
# cars groups by brands with the most models

most_makes = test2_2_dollarsnew %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  summarise(average_cost = (mean(Price)), average_predicted_cost = (mean(Predicted_price)))
```

```{r}
ecars

```


```{r}


gplt1 = ggplot(NULL, aes(Predicted_price, Price)) +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Predicted_price)) +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Predicted_price_lwr), col = 'red') +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Predicted_price_upr), col = 'red') +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Confidence_price_lwr), col = 'blue') +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Confidence_price_upr), col = 'blue') +
      ylim(0,250)+ 
geom_point(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Price), alpha = .5) +
geom_point(data = most_makes, aes(x = average_predicted_cost, y = average_cost), size = 3, shape = 23, fill = make_colors) +
 scale_color_manual(values = make_colors)

gplt1

ggsave('gplt1.png', width = 15)
         
```
```{r}
gplt1 = ggplot(NULL, aes(Predicted_price, Price)) +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Predicted_price)) +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Predicted_price_lwr), col = 'red') +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Predicted_price_upr), col = 'red') +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Confidence_price_lwr), col = 'blue') +
      geom_line(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Confidence_price_upr), col = 'blue') +
      ylim(0,250)+ 
      geom_point(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Price), alpha = .5) +
      geom_point(data = most_makes, aes(x = average_predicted_cost, y = average_cost), size = 3, shape = 23, fill = make_colors) +
      scale_color_manual(values = make_colors)

```

```{r}
test2_2_dollarsnew %>%
  arrange(Predicted_price)
```
```{r}
ecars
plot_ly(
  data = ecars_make,
  x = ~Price,
  type = "box",
  text = ~Car_name,
  tooltip = c("x", "text")
)

plot_ly(
  data = ecars_make,
  x = ~Price,
  y = ~Make,
  type = "box",
  color = ~Make,
  colors = make_colors,
  text = ~Car_name,
  tooltip = c("x", "text"),
  showlegend = FALSE
)
```

```{r}
options(repr.plot.width = 15, repr.plot.height =2) 

ggplot(data = test2_2_dollarsnew, aes(x = Predicted_price, y = Price)) +
  geom_point() +
  geom_line(aes(x = Predicted_price, y = Predicted_price)) +
  geom_line(aes(x = Predicted_price, y = Predicted_price_lwr), col = 'red') +
  geom_line(aes(x = Predicted_price, y = Predicted_price_upr)) +
  geom_line(aes(x = Predicted_price, y = Confidence_price_lwr)) +
  geom_line(aes(x = Predicted_price, y = Confidence_price_upr)) #+
 geom_point(aes(x = most_makes$average_cost, y =most_makes$average_predicted_cost))


  
new
```


```{r}
new
new %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  summarise(average_cost = (mean(Price)/1000), average_predicted_cost = (mean(Predicted_price)/1000)) #%>%
  #ggplot(., aes(x = Make, y = average_predicted_cost)) +
  #geom_col(aes(fill = Make)) + 
  #ylab('Average cost in Germany in thousands of Eruros')+
  #theme(axis.title.x=element_blank(),
   #     axis.text.x=element_blank(),
    #    axis.ticks.x=element_blank())
```
```{r}
new %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  summarise(average_price = (mean(Price)/1000), average_predicted_price =  (mean(Predicted_price)/1000))%>%
  ggplot(., aes(x = average_predicted_price, y = average_price)) +
  geom_point(aes(color = Make), size =4) 
  
```



```{r}
new
new %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  summarise(average_price = (mean(Price)/1000), average_predicted_price = (mean(Predicted_price)/1000))%>%
  ggplot(., aes(x = average_predicted_price, y = average_price)) +
  geom_point(aes(color = Make), size =4) +
  geom_line(aes(x = average_predicted_price, y = average_predicted_price)) + 


```

```{r}
predict(model, newdata, interval = 'confidence')
predict(model, newdata, interval = 'prediction')
```


```{r}
new
new %>% group_by(Make) %>%
  filter(n() >= 10) %>%
  summarise(average_price = (mean(Price)/1000), average_predicted_price = (mean(Predicted_price)/1000))
```

```{r}
ecars_missing_price
pre
```


```{r}
model
```
```{r}
ecars
```


```{r}
model.empty = lm(Price_pow ~ 1, data = ecars)
model.full = lm(Price_pow ~ Efficiency_pow + Range + Battery + Speed_pow + Fast_charge + Acceleration, data = ecars)
scope = list(lower = formula(model.empty), upper = formula(model.full))
scope
forwardAIC = step(model.empty, scope, direction = 'forward', k = 2)
```

battery speed_pow efficiency and fast charge 

```{r}
model.empty2 = lm(Price ~ 1, data = ecars)
model.full2 = lm(Price ~ Efficiency + Range + Battery + Top_speed + Fast_charge + Acceleration, data = ecars)
scope2 = list(lower = formula(model.empty2), upper = formula(model.full2))
scope2
forwardAIC2 = step(model.empty2, scope2, direction = 'forward', k = 2)
```


```{r}
model.empty3 = lm(Price_pow ~ 1, data = ecars)
model.full3 = lm(Price_pow ~ Efficiency + Range + Battery + Top_speed + Fast_charge + Acceleration, data = ecars)
scope3 = list(lower = formula(model.empty3), upper = formula(model.full3))
forwardAIC3 = step(model.empty3, scope3, direction = 'forward', k = 2)
```
I'm getting a lower AIC when I run these without transforming them??? I need to transform price but not the others?? not sure what to do?? 

```{r}
model.empty = lm(Price_pow ~ 1, data = ecars)
model.full = lm(Price_pow ~ Efficiency_pow + Range + Battery + Speed_pow + Fast_charge + Acceleration, data = ecars)
scope = list(lower = formula(model.empty), upper = formula(model.full))
scope
forwardAIC = step(model.empty, scope, direction = 'forward', k = 2)
```

```{r}
broom::glance(model)
broom::glance(model.full)
model_best = lm(Price_pow ~ Efficiency_pow + Range + Battery + Speed_pow + Fast_charge, data = ecars)
broom::glance(model.full3)
broom::glance(model_best)
```


```{r}
ecars
model_box = lm(Price ~ Top_speed + Range + Efficiency + Fast_charge + Acceleration, data = ecars)
summary(model_box)

```
```{r}
bc = boxCox(model_box)

lambda = bc$x[which(bc$y == max(bc$y))]
lambda
Price.bc = (ecars$Price^lambda - 1)/lambda
Price.bc
model.bc = lm(Price.bc ~ Top_speed + Range + Efficiency + Fast_charge + Acceleration, data = ecars)
              
summary(model.bc)
broom::glance(model.bc)

hist(Price.bc)
```
****This is how to undo the lambda transformation
```{r}
((Price.bc*lambda) + 1)^(1/lambda)
ecars$Price
```


```{r}
plot.new()
plot( x = 50, y = 54)
lines(predicted_price$Predicted, predicted_price$Predicted)
```

```{r}
ecars_missing_price
```






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